Fast leakage assessment

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Abstract

We describe a fast technique for performing the computationally heavy part of leakage assessment, in any statistical moment (or other property) of the leakage samples distributions. The proposed technique outperforms by orders of magnitude the approach presented at CHES 2015 by Schneider and Moradi. We can carry out evaluations that before took 90 CPU-days in 4 CPU-hours (about a 500-fold speed-up). As a bonus, we can work with exact arithmetic, we can apply kernel-based density estimation methods, we can employ arbitrary pre-processing functions such as absolute value to power traces, and we can perform information-theoretic leakage assessment. Our trick is simple and elegant, and lends itself to an easy and compact implementation. We fit a prototype implementation in about 130 lines of C code.

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Reparaz, O., Gierlichs, B., & Verbauwhede, I. (2017). Fast leakage assessment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10529 LNCS, pp. 387–399). Springer Verlag. https://doi.org/10.1007/978-3-319-66787-4_19

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